When it comes to hiring a new candidate for an open position, there are a lot of factors that come into play. What if there was a way to ensure that a new hire shares similar workplace values and has the proper qualifications? Using big data when it comes to recruiting and hiring new employees can help to find a mutually suitable candidate. It can lead to a more diverse workplace and can create a faster and less expensive process of recruitment.
With the answer to a seamless workforce available, why haven’t more companies jumped to create the most efficient teams possible?
People Analytics
People analytics uses data to diminish business problems and enhance outcomes at all levels of an organization. By applying proven math and data science techniques to human resources, people analytics can ensure that the individuals hired are the best fit for the company, job and team. The process combines hard science with an emotional component and predicts the relationship of employee and environment. These algorithms learn and adjust according to specific needs and characteristics of the organization and factors like emotions and personality are factored in along with job qualifications.
Retention and Job Satisfaction
There are two other equally salient advantages to employing people analytics: retention and job satisfaction. Consider the 2015 National Healthcare Retention & RN Staffing Report, which found that the past four years have seen a steady rise in hospital turnover rates. The current rate is 17.2 percent, up from 13.5 percent in 2011.
This is alarming, especially given that the cost of such turnover has a profound impact on a health care facility’s bottom line: Medicare reimbursement, for example, is tied to specific HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) scores.
The alarm bells ring even louder when one also considers that several recent surveys have shown that as many as 32 percent of American workers want to leave their jobs. In an economy filled with high unemployment rates, many workers feel trapped and unhappy in their current positions. Happy workers are the key to productivity, and employing people analytics during the hiring process can lead to a more dynamic workforce with lower turnover rates.
The Math of It All
Using proprietary algorithms, we have seen a remarkable turnaround. In over 135 health care facilities across the country with which we have partnered, the turnover rate has been reduced by a median of 38 percent, with the high of 100 percent. Even in the least successful job function in the least successful department in the least successful facility, the reduction was still 13 percent.
Human expertise will always be a part of employment recruitment, hiring and retention. However, incorporating people analytics will make the process more efficient and effective and result in a better experience for the hospital, its employees and patients.
Mike Rosenbaum is the Founder and CEO of Pegged Software. Pegged Software, which applies big data to hiring and team assembly, grew out of Mike’s work in academia and in the public sector. After having difficulty selling the core technology in Pegged in 2001, Mike started an IT services company called Catalyst IT Services as the first customer for the technology. After growing Catalyst meaningfully (Catalyst today has a headcount of approximately 250 and serves clients such as Nike, Starwood, Choice Hotels, JPMorgan Chase and Red Hat), Mike spun Pegged out as a separate company in 2010 to focus on licensing Pegged’s technology into the health care market. After deploying to seven early adopter clients in 2010, Pegged spent two years collecting data and iterating the product for the hospital and long-term care markets, and in 2012 started deploying beyond its initial customer base. Today, Pegged is deployed into 135 facilities and is processing over 3 million job applications per year.
Prior to starting Pegged Software, Mike Rosenbaum received an Irving R. Kaufman Fellowship to support his work building the first version of what is now Pegged’s analytics engine for talent selection. Before Pegged, Rosenbaum was a John M. Olin Fellow in Law and Economics at Harvard and served at the White House as an economist, at the U.S. Department of State on trade issues and issues related to the former Soviet Union and at Coopers & Lybrand in the Russian Federation on privatization and commercialization in the early 1990s. In addition to his academic work around what became Pegged Software, Rosenbaum’s publications and work focused on the application of data to the most subjective areas of human endeavors. His work was featured in the Stanford Law and Policy Review and the Harvard John M. Olin Fellow Center for Law, Economics and Business Series.
In the community, Rosenbaum serves as a Trustee of the Baltimore Museum of Art, where he currently chairs the search committee for the BMA’s next Director, and of Bryn Mawr School. He is a past Board Member of the Family Tree and the Leadership Council of the Open Society Institute, a former Chair of Maryland IT PAC, and a former President of the Harvard Club of Maryland.
Rosenbaum has a J.D. from Harvard Law School, an M.S. in Economics from the London School of Economics and Political Science and a B.A. from Harvard College.
